期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2020
卷号：V-3-2020
页码：401-408
DOI：10.5194/isprs-annals-V-3-2020-401-2020
语种：English
出版社：Copernicus Publications
摘要：The low operational cost of using freely available remote sensing data is a incentive for water agencies to complement their field campaigns and produce spatially distributed maps of some water quality parameters. The objective of this study is to compare the performance of Sentinel-2 MSI and Landsat-8 OLI sensors to produce multiple regression models of water quality parameters in a hydroelectric reservoir in Brazil. Physical-chemistry water quality parameters were measured iin loco/i using sensors and also analysed in laboratory from water samples collected simultaneously. The date of sampling corresponded to the almost simultaneous overflight of Sentinel-2B and Landsat-8 satellites which provided a means to perform a fair comparison of the two sensors. Four optically active parameters were considered: chlorophyll-a, Secchi disk depth, turbidity and temperature (the latter using Landsat-8 TIR sensor). Other six optically non-active parameters were also considered. The multiple regression models used the spectral reflectance bands from both sensors (separately) as predictors. The reflectance values were based on averaging kernels of 30thinsp;m and 90thinsp;m. Stepwise variable selection combined with ia priori/i knowledge based on other studies were used to optimize the choice of predictors. With the exception of temperature, the other optically active parameters yielded regression models from both the Sentinel and Landsat sensors, all with ir/isup2/supthinsp;gt;thinsp;0.75. The models for the optically non-active parameters produced less striking results with ir/isup2/sup as low as 0.03 (temperature) and as high or better than gt;thinsp;0.8 (pH and Dissolved oxygen).
